Interval Type-2 Fuzzy C-means Clustering using Intuitionistic Fuzzy Sets

被引：0

作者：

Dzung Dinh Nguyen ^{[1
]}

Long Thanh Ngo ^{[1
]}

Long The Pham ^{[1
]}

机构：

[1] Le Quy Don Tech Univ, Fac Informat Technol, Dept Informat Syst, 236 Hoang Quoc Viet, Hanoi, Vietnam

来源：

2013 THIRD WORLD CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGIES (WICT) | 2013年

关键词：

Intuitionistic fuzzy sets; intuitionistic type-2 fuzzy sets; Intuitionistic fuzzy c-means clustering; type-2 fuzzy c-means clustering; LOGIC SYSTEMS; ALGORITHM;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, intuitionistic interval type-2 fuzzy c-means clustering ( InIT2FCM) method is proposed for the clustering problems. Intuitionistic fuzzy sets ( IFS) and intuitionistic type-2 fuzzy sets ( InIT2FS) were introduced with the aim to better handle the uncertainty. Utilizing the advantages of the IFS and InT2FS, we have combined them with fuzzy clustering algorithms to overcome some drawbacks of the "conventional" FCM in handling uncertainty. The experiments were completed for different types of images which show the advantages of the proposed algorithms, especially with noisy images.

引用

页码：299 / 304

页数：6

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